Apply Aggregate Function to Array Column
Apply an element-wise aggregation function to an array column
(this is essentially a dplyr wrapper for the
aggregate(array<T>, A, function<A, T, A>[, function<A, R>]): R
built-in Spark SQL functions)
hof_aggregate( x, start, merge, finish = NULL, expr = NULL, dest_col = NULL, ... )
x |
The Spark data frame to run aggregation on |
start |
The starting value of the aggregation |
merge |
The aggregation function |
finish |
Optional param specifying a transformation to apply on the final value of the aggregation |
expr |
The array being aggregated, could be any SQL expression evaluating to an array (default: the last column of the Spark data frame) |
dest_col |
Column to store the aggregated result (default: expr) |
... |
Additional params to dplyr::mutate |
## Not run: library(sparklyr) sc <- spark_connect(master = "local") # concatenates all numbers of each array in `array_column` and add parentheses # around the resulting string copy_to(sc, tibble::tibble(array_column = list(1:5, 21:25))) %>% hof_aggregate( start = "", merge = ~ CONCAT(.y, .x), finish = ~ CONCAT("(", .x, ")") ) ## End(Not run)
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